A fuzzy logic based model proposal for smart supplier selection

Due to rapid developments of technology in recent years, the rate of globalization has increased. Under the growing globalization, it has become necessary for existing systems to be faster and more integrated in order to survive in every fields. In this situation, businesses have had to integrate their existing systems with these developments and new technologies in order to maintain their competitive capacity in the market that they are in. Supply chain management systems are one of the most important and must be managed correctly for businesses. In this study, supplier selection, which is one of the most important links in the management of supply chains, has been examined under economic, social, environmental and smart criterias. In the study, interval valued q-rung fuzzy number based MAIRCA (Multi Attributive Ideal-Real Comparative Analysis) meyhod has propose for a smart supplier selection of a sub-industry automotive company. 18 criterias under 4 main criteria were determined with the extensive literature reviews and past experiences of a team of 4 experts. The opinions of the experts were evaluated with the interval valued q-digit fuzzy number. A fuzzy number was proposed for the MAIRCA method, like the studies in the literature, but unlike the literature, the interval valued q-rung fuzzy number was applied to the MAIRCA method. The interval valued q-rung fuzzy number, which is an extension of the q-rung fuzzy number obtained by developing the heuristic fuzzy number and the pythagorean fuzzy number, provided more advantages in the evaluation of expert opinions. Keywords: MAIRCA, Multi criteria decision making methods, Smart supplier selection, Supplier selection, Supply chain, Interval valued q-rung fuzzy number